Data Analyst - MARVEL Strike Force

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Analyst – MARVEL Strike Force based in Canada. This is a remote opportunity to turn player and product data into insights that shape the future of a live-service mobile game. You’ll work closely with product, design, economy, live operations, marketing, and leadership teams to understand player behavior and business performance. The role combines hands-on SQL and Python analysis with reporting, experimentation, tracking, and strategic storytelling. You’ll help identify opportunities to improve engagement, retention, monetization, progression, and overall game health. Working in a fast-moving environment, you’ll balance analytical rigor with the need to make timely, practical recommendations. You’ll also have the opportunity to thoughtfully incorporate AI-enabled tools into modern analytics workflows while maintaining strong standards for data quality, privacy, and accuracy. Use AI-enabled tools responsibly to accelerate data exploration, SQL/Python development, documentation, quality assurance, summarization, and insight generation while validating outputs and maintaining sound analytical judgment. Partner with product, design, economy, live operations, marketing, and leadership teams to translate data into actionable recommendations that improve player engagement, retention, monetization, and long-term game health. Own recurring business-health reporting, delivering KPI analyses, trend context, variance explanations, and clear executive-ready narratives explaining what changed, why it changed, and recommended next steps. Analyze player behavior across onboarding, progression, live events, offers, combat modes, and other core game systems to identify risks, opportunities, and sources of player friction. Design and validate analytics tracking for new features, live events, player offers, and experiments to ensure accurate measurement from launch onward. Support experimentation and A/B testing by helping define appropriate metrics, evaluate statistical significance, monitor guardrail metrics, and interpret post-test results. Communicate complex analytical findings through concise, compelling data stories tailored to both technical and non-technical stakeholders. Work effectively in a live-service environment where priorities can shift quickly, data may be imperfect, and decisions require a combination of speed, rigor, and business judgment. Requirements Bachelor’s degree in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline; an advanced degree is an asset. At least 2 years of experience in data analytics, product analytics, business analytics, financial analysis, data science, or a comparable quantitative role. At least 2 years of hands-on experience using SQL and Python , including writing complex queries across multiple data sources. At least 2 years of experience creating reports and dashboards with Tableau, Looker, or a comparable business intelligence platform . Practical understanding of experimentation and A/B testing, including test design, metric selection, statistical significance, guardrail metrics, and post-test interpretation. Strong analytical thinking and the ability to distinguish meaningful patterns from incomplete, noisy, or imperfect data. Excellent communication and storytelling skills, with the ability to transform detailed analysis into clear and actionable recommendations. Curiosity and practical interest in AI-enabled analytics tools, combined with the judgment to validate outputs, protect sensitive information, and avoid unsupported conclusions. Comfortable collaborating across multiple functions and communicating effectively with both technical and non-technical stakeholders. Ability to operate successfully in a fast-paced live-service environment where priorities evolve and decisions often need to be made quickly. Familiarity with mod